absa_sentiment_classifier
This model is a fine-tuned version of yangheng/deberta-v3-base-absa-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2757
- Accuracy: 0.9410
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1904 | 1.0 | 296 | 0.2309 | 0.9359 |
| 0.0724 | 2.0 | 592 | 0.2757 | 0.9410 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1